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Synopsis

This unit focuses on the tools for a large, digital data world, including the building blocks for business analytics, modern insurance and risk assessment. A computational approach is employed to teach the concepts of statistics, and decision making in the presence of uncertainty. An important aspect will be to develop skills for compiling data from multiple sources to support better decisions and models. Topics covered will include simulation and randomisation methods, decision and credibility theory, data wrangling and visualisation, methods for time series, Bayesian analysis and models for risk and loss distributions.

Outcomes

The learning goals associated with this unit are to:

use simulation of statistical games to understand decision theory

learn about statistical distributions, including those used for loss functions

Assessment

Within semester assessment: 40% + Examination: 60%

Workload requirements

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.